Publications

Publications are in reversed chronological order. For a full list, please refer to Google Scholar

2024

  1. arXiv
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    VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images
    M Maruf, Arka Daw, Kazi Sajeed Mehrab, Harish Babu Manogaran, Abhilash Neog, and 17 more authors
    arXiv preprint, 2024
  2. arXiv
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    What Do You See in Common? Learning Hierarchical Prototypes over Tree-of-Life to Discover Evolutionary Traits
    Harish Babu Manogaran, M Maruf, Arka Daw, Kazi Sajeed Mehrab, Caleb Patrick Charpentier, and 8 more authors
    arXiv preprint, 2024
  3. ECCV
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    Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution
    Mridul Khurana, Arka Daw, M. Maruf, Josef C. Uyeda, Wasila Dahdul, and 10 more authors
    ECCV, 2024
  4. arXiv
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    Fish-Vista: A Multi-Purpose Dataset for Understanding & Identification of Traits from Images
    Kazi Sajeed Mehrab, M Maruf, Arka Daw, Harish Babu Manogaran, Abhilash Neog, and 6 more authors
    arXiv preprint arXiv:2407.08027, 2024
  5. AISY
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    Motion Enhanced Multi-Level Tracker (MEMTrack): A Deep Learning-Based Approach to Microrobot Tracking in Dense and Low-Contrast Environments
    Medha Sawhney, Bhas Karmarkar, Eric J Leaman, Arka Daw, Anuj Karpatne, and 1 more author
    Advanced Intelligent Systems, 2024
  6. ICML
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    Neuro-Visualizer: An Auto-encoder-based Loss Landscape Visualization Method
    Mohannad Elhamod, and Anuj Karpatne
    ICML, 2024

2023

  1. arXiv
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    Beyond Discriminative Regions: Saliency Maps as Alternatives to CAMs for Weakly Supervised Semantic Segmentation
    M Maruf, Arka Daw, Amartya Dutta, Jie Bu, and Anuj Karpatne
    arXiv preprint arXiv:2308.11052, 2023
  2. KDD
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    Discovering Novel Biological Traits From Images Using Phylogeny-Guided Neural Networks
    Mohannad Elhamod, Mridul Khurana, Harish Babu Manogaran, Josef C Uyeda, Meghan A Balk, and 6 more authors
    In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
  3. CVPR CV4Animals Workshop
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    Detecting and Tracking Hard-to-Detect Bacteria in Dense Porous Backgrounds
    Medha Sawhney, Bhas Karmarkar, Eric J Leaman, Arka Daw, Anuj Karpatne, and 1 more author
    In CVPR Workshop on CV4Animals 2023, 2023
  4. ICML
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    Mitigating propagation failures in physics-informed neural networks using retain-resample-release (r3) sampling
    Arka Daw, Jie Bu, Sifan Wang, Paris Perdikaris, and Anuj Karpatne
    arXiv preprint arXiv:2207.02338, 2023
  5. arXiv
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    Let There Be Order: Rethinking Ordering in Autoregressive Graph Generation
    Jie Bu, Kazi Sajeed Mehrab, and Anuj Karpatne
    arXiv preprint arXiv:2305.15562, 2023

2022

  1. IEEE BigData
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    Multi-task Learning for Source Attribution and Field Reconstruction for Methane Monitoring
    Arka Daw, Kyongmin Yeo, Anuj Karpatne, and Levente Klein
    In 2022 IEEE International Conference on Big Data (Big Data), 2022
  2. TIST
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    CoPhy-PGNN: Learning physics-guided neural networks with competing loss functions for solving eigenvalue problems
    Mohannad Elhamod, Jie Bu, Christopher Singh, Matthew Redell, Abantika Ghosh, and 3 more authors
    ACM Transactions on Intelligent Systems and Technology, 2022
  3. Book Chapter
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    Physics-Guided Neural Networks (PGNN): An Application in Lake Temperature Modeling
    Arka Daw, Anuj Karpatne, D. Watkins William, Jordan S. Read, and Vipin Kumar
    In Knowledge Guided Machine Learning, 2022
  4. Methods in Ecology and Evolution
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    Hierarchy-guided Neural Networks for Species Classification
    Mohannad Elhamod, Kelly M. Diamond, A. Murat Maga, Yasin Bakis, Henry L. Bart, and 6 more authors
    Methods in Ecology and Evolution, 2022

2021

  1. NeurIPS
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    Learning compact representations of neural networks using discriminative masking (DAM)
    Jie Bu, Arka Daw, M Maruf, and Anuj Karpatne
    Advances in Neural Information Processing Systems, 2021
  2. ITSC
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    A graph convolutional neural network based approach for traffic monitoring using augmented detections with optical flow
    Ioannis Papakis, Abhijit Sarkar, and Anuj Karpatne
    In 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021
  3. KDD
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    PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics
    Arka Daw, M Maruf, and Anuj Karpatne
    In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021

2020

  1. Big Data
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    Physics-Guided Deep Learning for Drag Force Prediction in Dense Fluid-Particulate Systems
    Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, and 2 more authors
    Big Data, 2020
    PMID: 33090021
  2. arXiv
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    Gcnnmatch: Graph convolutional neural networks for multi-object tracking via sinkhorn normalization
    Ioannis Papakis, Abhijit Sarkar, and Anuj Karpatne
    arXiv preprint arXiv:2010.00067, 2020
  3. SDM
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    Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling
    Arka Daw, R. Quinn Thomas, Cayelan C. Carey, Jordan S. Read, Alison P. Appling, and 1 more author
    In Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

2019

  1. SDM
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    Physics-guided design and learning of neural networks for predicting drag force on particle suspensions in moving fluids
    Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, and 2 more authors
    arXiv preprint arXiv:1911.04240, 2019